Aside

logo

Contact

Tech Skills

R / tidyverse
Python3
Bash / awk
Git
SQL
Docker
AWS
LaTeX

Other Skills

Data visualisation
Reproducible research
Documentation writing



For fun I like to

-attend in BristolR and PyData meetups
-listen to Data Science podcasts
-participate in hackathons / data challenges



See full CV at marinalearning.netlify.com/cv

Made w/ pagedown.

Last updated on 2020-05-17.

Main

Marina Vabistsevits

Doctoral student at the University of Bristol, working in the interdisiplinary research applying data mining methods to answer epidemological questions

Education

PhD, Data mining in Epidemiology

University of Bristol

Bristol, UK

2023 - 2019

MSc, Bioinformatics

University of Copenhagen

Copenhagen, Denmark

2017 - 2015

BSc, Biochemistry

University of Bath

Bath, UK

2015 - 2011

Research Experience

Doctoral Student

MRC Intergative Epidemiology Unit

University of Bristol

2023 - 2019

  • Mini-project 1: Implemented a generalisable R workflow of performing multivariate correlation analysis (metaCCA) on several GWAS, using summary statistics from MR-Base, in order to find pleiotropic variants across the measured traits
  • Mini-project 2: Carried out a Mendelian Randomisation study to investigate the mechanism mediating the effect of early life BMI on breast cancer risk
  • Main PhD project: Will be working with EpiGraphDB, a graph database, to answer causal relationship questions in epidemiology using data mining methods

Visiting Researcher / Master’s Thesis Student

Danish Cancer Research Centre

Copenhagen, Denmark

2017 - 2016

  • Explored TCGA breast cancer gene expression RNA-Seq data to identify the involvement of autophagy-related genes in certain disease subtypes.
  • Performed extensive EDA, followed by differential expression analysis and enrichment analysis, allowing me to find over-represented autophagy genes

Industry Experience

Bioinformatician

Living DNA

Frome, UK

2019 - 2017

  • Led the research work on improving the ancestry reference panels used by the core pipeline behind the company’s direct-to-consumer ancestry genetics test, bringing considerable improvement to results accuracy
  • Gained experience in working with a legacy codebase through maintaining and contributing to the in-house pipelines (Python)
  • Honed my R programming skills by switching to tidyverse approach and advanced my data visualisation skills

Student research assistant in the Big Data group

3Shape

Copenhagen, Denmark

2017 - 2016

  • Performed data preparation and visualisation tasks in Python, gaining practical experience of programming in a professional environment
  • Used deep learning framework Caffe2 to develop a neural network training pipeline for scan image classification tasks

Placement Student in Bioinformatics team

Oxford Gene Technology

Oxford, UK

2014 - 2013

  • Became responsible for a multitude of exome- and RNA-seq projects, running in-house data analysis pipelines and performing custom analysis for different projects